Forward-thinking retailers are beginning to use exogenous data such as weather data and data generated on Facebook or Twitter to create data mashups with internal data such as sales data.

In fact, according to Gartner, over the next few years, leading organizations will link analytic initiatives to financial objectives, increase investments in advanced analytics, and incorporate a wider range of exogenous data.

Gartner predicts that by 2019, 75% of analytics solutions will incorporate 10 or more exogenous data sources from second-party partners or third-party providers.

Now, because of the ever-present smartphone and social media, shoppers can access real-time weather updates alongside information on sales and new products.

Shoppers can make purchases anywhere, anytime on mobile devices, and easily share opinions and reviews on products.

As an example, consider how exogenous data such as weather data and social data impacted the 2015 holiday shopping season:

51% of holiday shoppers reported plans to get gift ideas from social media, while 50% of shoppers intended to find holiday discounts and sales through social media. (Deloitte University Press, 2015)

Six of 10 consumers planned to check the weather forecast before holiday shopping. (The Weather Company, 2015)

All across the eastern U.S. holiday shoppers left their down jackets at home during their 2015 holiday shopping, while they experienced one of the warmest combined November and December on record.

Customer Engagement: Social media platforms such as Twitter have opened a world of opportunity for retailers to directly engage with customers. Moving beyond social listening and push marketing, leading companies are now using social platforms as “early warning systems” to understand how, when and why to engage with customers. For example, retailers can engage consumers with special deals and opportunities just for social media users and monitor and analyze relevant conversations to better understand customer’s likes and dislikes.

Supply chain efficiency: One global retailer is using the combination of internal and real-time public data, including weather, competitors’ promotions, Twitter feeds, economic data and the news, to identify strong, yet counter intuitive, demand signals. It developed an algorithmic-based situation engine to provide exception forecasts for certain products whose trend and seasonal forecasts do not capture accurate projection. The result: The company fundamentally reoriented its massive supply chain to deliver merchandise based on these real-time forecasts.

The connection between consumers, buying behavior and the weather, coupled with social media, powerful predictive analytics and cognitive computing capabilities, is creating a vast opportunity for businesses to create their own data mashup, understand it and put it to use.

The data mashup is and will continue to be a powerful strategy for retailers in an extremely competitive industry—not just during the holiday shopping season, but during every shopping season.

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